A massive Multiple Input Multiple Output (MIMO) system corresponds to a system for improving throughput by installing a plurality of antennas in an eNB. According to the massive MIMO system, a high data rate used in a next-generation communication system subsequent to 4th generation may be easily satisfied by only a simple linear precoder. In theory, in a case of using a large number of antennas, various problems which limit throughput of the system, such as fast fading, inter-user interference, and the like may be perfectly removed by using the linear precoder. That is, when a multiple user system based on the massive MIMO is configured, throughput of this system, which is much higher than that of an existing communication system, may be obtained by low costs.
Such an advantage of the massive MIMO system is based on assumption that the eNB knows channel information. However, in a situation where there are a large number of antennas, such an assumption is very burdensome to the system. Thus, researches on an existing massive MIMO system are performed based on a Time-Division Duplex (TDD) system in which channel estimation costs are not affected by the number of antennas of the eNB mainly due to channel reciprocity.
When data transmission amounts of UpLink (UL) and DownLink (DL) are similar to each other or a distance between a transmission end and a reception end is large, the TDD system has a frequency efficiency lower than that of a Frequency-Division Duplex (FDD) system due to conversion between a transmission mode and a reception mode. Accordingly, an existing communication system such as a Universal Mobile Telecommunications System (UMTS), Wideband Code Division Multiple Access (WCDMA), Code Division Multiple Access 2000 (CDMA2000), and the like has supported the FDD mode in various environments. Thus, researches and development on a FDD massive MIMO system for securing backward compatibility are a necessary and sufficient condition which allows the massive MIMO system to be a core technology of the next-generation communication system.
In the FDD system, channel correlation is not established. Thus, the FDD system uses a limited feedback system which quantizes a channel estimated by the reception end and transmits the quantized channel to the transmission end, in order to secure Channel State Information at the Transmitter (CSIT). Existing researches on the limited feedback show that a size of a codebook for restraining system throughput deterioration caused by the limited feedback in a single stream (or Single User (SU)) environment exponentially increases according to the number of transmission antennas. A size of a codebook needed when an environment of the system is expanded to a multiple stream (or Multiple User; MU) environment also increases according to a Signal-to-Noise Ratio (SNR) as well as the number of transmission antennas. These facts suggest that the number of pilot signals, feedback channel capacity, and the size of the codebook, and the like will become main factors which restrain throughput of the FDD massive MIMO system. Especially, in the FDD massive MIMO system, the UL may obtain a high array gain based on channel estimation, such that it is likely that a cause of a bottleneck of the system is the size of the codebook rather than the feedback channel capacity.
FIG. 1 illustrates a configuration of a wireless communication system. Referring to FIG. 1, in an FDD communication system according to the related art, in order to estimate a channel at a transmission end, reception ends User 1 to User K quantize an estimated channel by using a Channel Quality Indicator (CQI) and a Precoding Matrix Indicator (PMI) and then feedback indexes obtained by the quantization to a transmission end. The transmission end determines a coding technique and a modulation order based on the received CQI, determines a proper precoder based on the received PMI, and transmits a signal according to the determined content. The PMI among information fed back to the transmission end includes information on a direction of each channel, various codebook generation algorithms such as a Grassmannian codebook, a Discrete Fourier Transform (DFT) codebook, and the like are proposed in order to minimize a Channel Estimation Error (CEE) caused by the PMI quantization.
It is assumed that B feedback bits are allocated for the PMI and a codebook having a size of N=2B is used. A case (perfect CSIT) CCSIT(P) where the transmission end perfectly knows the channel when a SU having a single antenna is serviced by using a Matched Filter (MF) and capacity throughput of CFB(P) when the transmission end estimates the channel by using the limited feedback system according to the related art are expressed by Equation (1) and Equation (2).CCSIT(P)=Eh{log2(1+P∥h∥2)}  (1)CFB(P)=Eh,W{log2(1+P∥h∥2 cos2(∠(h,w)))}≧Eh{log2(1+P∥h∥2(1−2−B/(M-1)))}  (2)
Here, P denotes a power of a transmission signal, and variance of noise is assumed to be 1. Equation (1) and Equation (2) imply that SNR loss caused by the limited feedback in a single stream or SU situation is a value corresponding to −10 log10(1−2−B/(M-1)dB as compared with perfect CSIT. That is, when B is equal to MT−1, a constant throughput loss as compared with the perfect CSIT may be maintained through the limited feedback system regardless of the SNR. When multiple streams or MUs are serviced based on a Zero-Forcing (ZF) filter, a difference between capacity throughputs of the perfect CSIT and the limited feedback system is expressed by Equation (3).ΔC(P)=CCSIT(P)−CFB(P)=MT log2(1+P·2−B/(MT−1))  (3)
Referring to Equation (3), when multiple streams are transmitted in the limited feedback system according to the related art, the size of the codebook needed for entirely securing a throughput gain according to an increase in the SNR may also increase according to the SNR as well as the number of transmission antennas.
FIG. 2A is a graph depicting a relation between the SNR and the data rate according to the CSIT, in a single user environment.
FIG. 2B is a graph depicting a relation between the SNR and the data rate according to the CSIT, in an MU environment.
As can be seen with reference to FIGS. 2A and 2B, when the multiple streams are transmitted, in a case where the size B of the codebook is fixed, there remains inter-UE interference even when the SNR increases, such that the throughput converges to a specific value. This implies that it may be impossible to efficiently remove interference through the linear precoder in the massive MIMO system when the limited feedback according to the related art is applied. Due to this characteristic, even when the SNRs of User Equipment (UEs) are excellent, there are disadvantages in that probability to be operated in an SU mode increases and a cell yield rate decreases.